Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "171"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 171 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 57 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 55 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 171, Node N16:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459872 not_connected 100.00% 0.00% 0.00% 0.00% - - 1.884049 4.912056 12.365147 1.845614 3.484387 8.313352 -0.162875 -0.207770 0.6436 0.5984 0.3946 nan nan
2459871 not_connected 100.00% 0.00% 0.00% 0.00% - - 1.442559 3.732227 12.113700 1.293007 1.950088 6.692150 -0.228472 -0.157914 0.6473 0.5934 0.3954 nan nan
2459870 not_connected 100.00% 0.00% 0.00% 0.00% - - 3.207992 6.824728 8.863296 0.153703 1.680255 2.430574 -0.210716 -0.455092 0.6515 0.5994 0.3973 nan nan
2459869 not_connected 100.00% 0.00% 0.00% 0.00% - - 2.657319 4.703965 8.637600 -0.051622 2.296967 4.122188 0.853848 0.000073 0.6661 0.6281 0.3873 nan nan
2459868 not_connected 100.00% 0.00% 0.00% 0.00% - - 3.025237 6.695055 13.259288 1.374835 0.804435 3.966367 0.132027 0.238495 0.6391 0.5930 0.4039 nan nan
2459867 not_connected 100.00% 0.00% 0.00% 0.00% - - 1.781389 4.539614 10.918191 0.795694 0.361868 1.445325 0.071505 -0.300717 0.6507 0.5971 0.4075 nan nan
2459866 not_connected 100.00% 0.00% 0.00% 0.00% - - 2.108443 5.228848 6.648317 0.836164 0.031894 0.916199 -0.491115 -0.106036 0.6547 0.5986 0.4004 nan nan
2459865 not_connected 100.00% 0.00% 0.00% 0.00% - - 3.816222 8.846026 13.330809 0.074793 3.046104 7.519515 3.361318 1.802151 0.6768 0.6083 0.3822 nan nan
2459864 not_connected 100.00% 0.00% 0.00% 0.00% - - 2.823867 9.087409 5.769161 -0.992969 0.395646 4.038380 0.985973 1.243318 0.6523 0.5786 0.4233 nan nan
2459863 not_connected 100.00% 0.00% 0.00% 0.00% - - 0.612971 4.869763 -1.132752 -0.851700 -0.495423 -0.707105 -0.494537 0.072719 0.6461 0.5677 0.4158 nan nan
2459862 not_connected 100.00% 0.00% 0.00% 0.00% - - 1.237445 5.381482 9.955387 0.819685 0.658258 6.124185 -0.210676 -0.413593 0.6301 0.5993 0.4200 nan nan
2459861 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.017515 2.907672 -2.166507 -0.445803 -1.194739 -2.142464 -0.543855 -0.507064 0.6624 0.5758 0.4291 nan nan
2459860 not_connected 100.00% 0.00% 0.00% 0.00% - - 0.427463 3.288814 7.626267 0.058157 1.262290 4.523127 -0.171642 -0.564387 0.6728 0.5888 0.4262 nan nan
2459859 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.254313 2.473893 -2.576792 0.366808 -0.830720 -1.802992 -0.309750 -0.098712 0.6773 0.5916 0.4247 nan nan
2459858 not_connected 0.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.322313 2.570858 -2.728890 0.213363 -0.914839 -1.171654 -0.399993 -0.236156 0.6873 0.5973 0.4363 2.554990 2.081126
2459857 not_connected 0.00% 100.00% 100.00% 0.00% - - 1.822536 3.373211 1.520690 1.331699 -0.430601 0.083682 -1.504822 -2.130699 0.0292 0.0293 0.0006 nan nan
2459856 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.893962 5.024504 7.146122 -0.148006 -0.309535 1.642503 -0.607468 -0.371254 0.6804 0.6161 0.4219 2.763073 2.195293
2459855 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.651843 5.539403 7.928781 0.385077 -0.521077 1.326300 -0.660695 -0.579060 0.6517 0.6295 0.4432 2.749630 2.150417
2459854 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.361715 5.907096 5.728786 -0.565681 -0.663239 1.700806 -0.627484 -0.637082 0.6770 0.6360 0.4606 2.799796 2.118599
2459853 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.818240 5.441394 9.358166 -0.049308 -0.064410 1.785154 -0.364690 -0.317444 0.7051 0.5908 0.4530 3.352257 2.266019
2459852 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.002164 6.621582 9.256279 0.134002 4.078278 3.987862 7.074828 2.327156 0.7997 0.7750 0.2649 3.955265 3.532607
2459851 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459850 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.817908 6.878561 8.879559 -0.043857 0.828945 5.875766 -0.200465 3.071102 0.7086 0.6707 0.3702 2.803273 2.092635
2459849 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.042386 6.070842 18.169478 0.526725 0.515386 2.644560 -0.222885 0.331244 0.7054 0.6600 0.3877 3.569105 2.762000
2459848 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.254984 4.412662 11.036468 0.562507 1.436585 6.080866 -0.204221 -0.394177 0.6829 0.6756 0.3948 2.794286 2.288513
2459847 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.339975 5.012668 10.452231 0.904618 0.518877 9.736389 -0.517150 -0.508381 0.6863 0.5957 0.4496 3.338619 2.427621

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 171: 2459872

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 12.365147 4.912056 1.884049 1.845614 12.365147 8.313352 3.484387 -0.207770 -0.162875

Antenna 171: 2459871

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 12.113700 3.732227 1.442559 1.293007 12.113700 6.692150 1.950088 -0.157914 -0.228472

Antenna 171: 2459870

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 8.863296 3.207992 6.824728 8.863296 0.153703 1.680255 2.430574 -0.210716 -0.455092

Antenna 171: 2459869

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 8.637600 2.657319 4.703965 8.637600 -0.051622 2.296967 4.122188 0.853848 0.000073

Antenna 171: 2459868

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 13.259288 3.025237 6.695055 13.259288 1.374835 0.804435 3.966367 0.132027 0.238495

Antenna 171: 2459867

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 10.918191 1.781389 4.539614 10.918191 0.795694 0.361868 1.445325 0.071505 -0.300717

Antenna 171: 2459866

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 6.648317 5.228848 2.108443 0.836164 6.648317 0.916199 0.031894 -0.106036 -0.491115

Antenna 171: 2459865

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 13.330809 3.816222 8.846026 13.330809 0.074793 3.046104 7.519515 3.361318 1.802151

Antenna 171: 2459864

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected nn Shape 9.087409 9.087409 2.823867 -0.992969 5.769161 4.038380 0.395646 1.243318 0.985973

Antenna 171: 2459863

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected nn Shape 4.869763 0.612971 4.869763 -1.132752 -0.851700 -0.495423 -0.707105 -0.494537 0.072719

Antenna 171: 2459862

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 9.955387 1.237445 5.381482 9.955387 0.819685 0.658258 6.124185 -0.210676 -0.413593

Antenna 171: 2459861

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected nn Shape 2.907672 2.907672 -0.017515 -0.445803 -2.166507 -2.142464 -1.194739 -0.507064 -0.543855

Antenna 171: 2459860

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 7.626267 0.427463 3.288814 7.626267 0.058157 1.262290 4.523127 -0.171642 -0.564387

Antenna 171: 2459859

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected nn Shape 2.473893 -0.254313 2.473893 -2.576792 0.366808 -0.830720 -1.802992 -0.309750 -0.098712

Antenna 171: 2459858

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected nn Shape 2.570858 2.570858 -0.322313 0.213363 -2.728890 -1.171654 -0.914839 -0.236156 -0.399993

Antenna 171: 2459857

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected nn Shape 3.373211 3.373211 1.822536 1.331699 1.520690 0.083682 -0.430601 -2.130699 -1.504822

Antenna 171: 2459856

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 7.146122 0.893962 5.024504 7.146122 -0.148006 -0.309535 1.642503 -0.607468 -0.371254

Antenna 171: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 7.928781 5.539403 1.651843 0.385077 7.928781 1.326300 -0.521077 -0.579060 -0.660695

Antenna 171: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected nn Shape 5.907096 5.907096 1.361715 -0.565681 5.728786 1.700806 -0.663239 -0.637082 -0.627484

Antenna 171: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 9.358166 5.441394 0.818240 -0.049308 9.358166 1.785154 -0.064410 -0.317444 -0.364690

Antenna 171: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 9.256279 3.002164 6.621582 9.256279 0.134002 4.078278 3.987862 7.074828 2.327156

Antenna 171: 2459851

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Shape nan nan nan inf inf nan nan nan nan

Antenna 171: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 8.879559 0.817908 6.878561 8.879559 -0.043857 0.828945 5.875766 -0.200465 3.071102

Antenna 171: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 18.169478 1.042386 6.070842 18.169478 0.526725 0.515386 2.644560 -0.222885 0.331244

Antenna 171: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 11.036468 4.412662 1.254984 0.562507 11.036468 6.080866 1.436585 -0.394177 -0.204221

Antenna 171: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
171 N16 not_connected ee Power 10.452231 5.012668 1.339975 0.904618 10.452231 9.736389 0.518877 -0.508381 -0.517150
In [ ]: